{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-01-08T14:45:19.182222Z",
     "start_time": "2025-01-08T14:45:19.013241Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 1. 数据生成\n",
    "X, y = make_classification(n_samples=200, n_features=2, n_informative=2, n_redundant=0,n_classes=2,\n",
    "                           n_clusters_per_class=1, weights=[0.3,0.3,0.4], flip_y=0, random_state=42)\n",
    "\n",
    "# 2. 初始化参数\n",
    "w = np.array([0.0, 0.0])  # 初始权重向量\n",
    "b = 0.0  # 初始偏置\n",
    "learning_rate = 0.01  # 学习率\n",
    "epochs = 1000  # 训练轮数\n",
    "\n",
    "# 3. 定义 Sigmoid 函数\n",
    "def sigmoid(z):\n",
    "    return 1 / (1 + np.exp(-z))\n",
    "\n",
    "# 4. 定义交叉熵损失函数\n",
    "def binary_cross_entropy(y_true, y_pred):\n",
    "    y_pred = np.clip(y_pred, 1e-15, 1 - 1e-15)  # 避免 log(0)\n",
    "    return -np.mean(y_true * np.log(y_pred) + (1 - y_true) * np.log(1 - y_pred))\n",
    "\n",
    "# 5. 手动训练逻辑回归模型（单样本更新）\n",
    "def train_model(features, labels, learning_rate, epochs):\n",
    "    w = np.array([0.0, 0.0])  # 初始权重向量\n",
    "    b = 0.0  # 初始偏置\n",
    "    losses = []\n",
    "    \n",
    "    for epoch in range(epochs):\n",
    "        epoch_loss = 0.0\n",
    "        for i in range(len(features)):\n",
    "            feature = features[i]\n",
    "            label = labels[i]\n",
    "\n",
    "            # 计算线性组合和预测概率\n",
    "            z = np.dot(w, feature) + b\n",
    "            probability = sigmoid(z)\n",
    "\n",
    "            # 计算损失\n",
    "            loss = binary_cross_entropy(np.array([label]), np.array([probability]))\n",
    "            epoch_loss += loss\n",
    "\n",
    "            # 计算梯度\n",
    "            dz = probability - label  # 损失对 z 的导数\n",
    "            dw = dz * feature  # 损失对 w 的导数\n",
    "            db = dz  # 损失对 b 的导数\n",
    "            \n",
    "            # 更新参数\n",
    "            w -= learning_rate * dw\n",
    "            b -= learning_rate * db\n",
    "        \n",
    "        losses.append(epoch_loss / len(features))\n",
    "    \n",
    "    return w, b, losses\n",
    "\n",
    "# 6. 可视化分类边界\n",
    "def plot_decision_boundary(X, y, w, b, title):\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    plt.scatter(X[:, 0], X[:, 1], c=y, cmap='coolwarm', marker='o', edgecolor='k')\n",
    "    \n",
    "    # 绘制决策边界\n",
    "    x_values = np.linspace(np.min(X[:, 0]), np.max(X[:, 0]), 100)\n",
    "    if w[1] != 0:  # 确保分母不为零\n",
    "        y_values = -(w[0] * x_values + b) / w[1]\n",
    "    else:\n",
    "        y_values = np.zeros_like(x_values)  # 如果 w[1] == 0，说明边界是垂直的\n",
    "    \n",
    "    plt.plot(x_values, y_values, color='black', linestyle='-', linewidth=2, label='Decision Boundary')\n",
    "    plt.xlabel('Feature 1')\n",
    "    plt.ylabel('Feature 2')\n",
    "    plt.title(title)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "# 7. 训练前的初始状态\n",
    "plot_decision_boundary(X, y, w, b, 'Initial Decision Boundary')\n",
    "\n",
    "# 8. 训练模型\n",
    "w_trained, b_trained, losses = train_model(X, y, learning_rate, epochs)\n",
    "\n",
    "# 9. 训练后的状态\n",
    "plot_decision_boundary(X, y, w_trained, b_trained, 'Trained Decision Boundary')\n",
    "\n",
    "# 10. 可视化训练过程中的损失变化\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.plot(range(1, epochs + 1), losses, label='Loss')\n",
    "plt.xlabel('Epochs')\n",
    "plt.ylabel('Loss')\n",
    "plt.title('Training Loss Over Epochs')\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "ValueError",
     "evalue": "shapes (3,) and (2,) not aligned: 3 (dim 0) != 2 (dim 0)",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mValueError\u001B[0m                                Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[32], line 81\u001B[0m\n\u001B[0;32m     78\u001B[0m plot_decision_boundary(X, y, w, b, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mInitial Decision Boundary\u001B[39m\u001B[38;5;124m'\u001B[39m)\n\u001B[0;32m     80\u001B[0m \u001B[38;5;66;03m# 8. 训练模型\u001B[39;00m\n\u001B[1;32m---> 81\u001B[0m w_trained, b_trained, losses \u001B[38;5;241m=\u001B[39m \u001B[43mtrain_model\u001B[49m\u001B[43m(\u001B[49m\u001B[43mX\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43my\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mlearning_rate\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mepochs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m     83\u001B[0m \u001B[38;5;66;03m# 9. 训练后的状态\u001B[39;00m\n\u001B[0;32m     84\u001B[0m plot_decision_boundary(X, y, w_trained, b_trained, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mTrained Decision Boundary\u001B[39m\u001B[38;5;124m'\u001B[39m)\n",
      "Cell \u001B[1;32mIn[32], line 38\u001B[0m, in \u001B[0;36mtrain_model\u001B[1;34m(features, labels, learning_rate, epochs)\u001B[0m\n\u001B[0;32m     35\u001B[0m label \u001B[38;5;241m=\u001B[39m labels[i]\n\u001B[0;32m     37\u001B[0m \u001B[38;5;66;03m# 计算线性组合和预测概率\u001B[39;00m\n\u001B[1;32m---> 38\u001B[0m z \u001B[38;5;241m=\u001B[39m \u001B[43mnp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mdot\u001B[49m\u001B[43m(\u001B[49m\u001B[43mw\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mfeature\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;241m+\u001B[39m b\n\u001B[0;32m     39\u001B[0m probability \u001B[38;5;241m=\u001B[39m sigmoid(z)\n\u001B[0;32m     41\u001B[0m \u001B[38;5;66;03m# 计算损失\u001B[39;00m\n",
      "\u001B[1;31mValueError\u001B[0m: shapes (3,) and (2,) not aligned: 3 (dim 0) != 2 (dim 0)"
     ]
    }
   ],
   "execution_count": 32
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-08T14:55:32.090218Z",
     "start_time": "2025-01-08T14:55:31.992265Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# Step 2: Generate a three-class classification dataset\n",
    "X, y = make_classification(n_samples=100, n_features=2, n_redundant=0, n_informative=2,\n",
    "                           n_classes=3, n_clusters_per_class=1, random_state=1)\n",
    "\n",
    "# Step 3: Split the data into training and test sets and fit the logistic regression model\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)\n",
    "clf = LogisticRegression(multi_class='multinomial', solver='lbfgs').fit(X_train, y_train)\n",
    "\n",
    "# Step 4: Plot the decision boundary. For that, we will assign a color to each point in the mesh [x_min, x_max]x[y_min, y_max].\n",
    "x_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\n",
    "y_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\n",
    "h = .02  # step size in the mesh\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
    "Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "\n",
    "# Put the result into a color plot\n",
    "Z = Z.reshape(xx.shape)\n",
    "plt.figure(1, figsize=(8, 6))\n",
    "plt.pcolormesh(xx, yy, Z, cmap=plt.cm.Paired, shading='auto')\n",
    "\n",
    "# Plot also the training points\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k', cmap=plt.cm.Paired)\n",
    "plt.xlabel('Feature 1')\n",
    "plt.ylabel('Feature 2')\n",
    "\n",
    "plt.xlim(xx.min(), xx.max())\n",
    "plt.ylim(yy.min(), yy.max())\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "\n",
    "plt.title('Multiclass Logistic Regression Decision Boundaries')\n",
    "plt.show()"
   ],
   "id": "3cec5ea04a30b1f9",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\python\\pytorch-learn\\venv\\Lib\\site-packages\\sklearn\\linear_model\\_logistic.py:1247: FutureWarning: 'multi_class' was deprecated in version 1.5 and will be removed in 1.7. From then on, it will always use 'multinomial'. Leave it to its default value to avoid this warning.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 35
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "26003028cb86853b"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
